Universität Wien

040088 UE Empirical Methods I (MA) (2020W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Summary

1 Lego , Moodle
2 Meissner , Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Registration information is available for each group.

Groups

Group 1

Pre-requisites:

Admission to the Master's programme

Attendance:

As part of the course grade, your class participation will be assessed every session. You will automatically fail the class if you miss more than 10% of sessions.

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

* Due to the current situation, this course is held in a fully digital form!

  • Tuesday 27.10. 16:45 - 20:00 Digital
  • Tuesday 03.11. 16:45 - 18:15 Digital
    Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 03.11. 18:30 - 20:00 Digital
    Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 10.11. 16:45 - 20:00 Digital
    Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 17.11. 16:45 - 20:00 Digital
  • Tuesday 24.11. 16:45 - 20:00 Digital
  • Tuesday 01.12. 16:45 - 20:00 Digital
  • Tuesday 15.12. 16:45 - 20:00 Digital
  • Monday 11.01. 16:45 - 18:15 Digital
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 19.01. 16:45 - 20:00 Digital
    Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 26.01. 16:45 - 20:00 Digital
    Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

Aims, contents and method of the course

This course is an introductory class on empirical methods and data analysis which precedes the follow-up class “Empirical Methods II”. The goal of this introductory course is for students to learn the fundamental techniques and obtain the basic skills required in empirical research. Our theoretical sessions will cover tools and stages required for running empirical projects (e.g. research design, measurement, methods of data collection) with a special focus on the pre-evaluation stage of an empirical work. Our applied sessions will introduce the students to basic programming skills, allowing them to prepare their data for analysis using statistical programming software. Students will participate by reading and presenting scientific articles in some of the highest ranked strategy journals. Knowledge gained in this course is also applied during a project where students actively develop the necessary steps for conducting their own empirical research projects.

Please note that as of now, the class will be held in-person (offline). Should the current situation not allow classroom teaching, an alternative solution (taking into account the need for STATA software) will be discussed.

Assessment and permitted materials

Students will be assessed based on their class participation (class work, home assignments and a presentation of an empirical paper), a written exam and an empirical project (own paper and a presentation of own findings). The final project (including presentation) accounts for 35%, the exam for 35% and class participation accounts for 30% of the final grade.

Minimum requirements and assessment criteria

Please be aware that attendance during the first session of this course is absolutely mandatory. If students miss the first session without contacting the lecturer in writing (at the very latest until 24 hours before the first session), giving a relevant reason/proof (e.g. illness=doctor's certificate, exam=confirmation by the examiner) for their absence, they will be deregistered from the course and their place will automatically be awarded to the next in line on the waiting list. After that, students are allowed to miss 10% of the classes without any consequences (2.25 hours). Exceeding this threshold would result in failing the class. In order to pass the course, at least 50% of the total 100% are required. Please note that TURNITIN will be used in order to test all written coursework (e.g. the final project) for possible plagiarism.
Grading scheme: [0%;50%) [50%;62.5%) [62.5%;75%) [75%;87.5%) [87.5%;100%]

Reading list

Necessary literature will be discussed in class.
https://strategy.univie.ac.at/

Group 2

Pre-requisites:

Admission to the Master's programme

Attendance:

As part of the course grade, your class participation will be assessed every session. You will automatically fail the class if you miss more than 10% of sessions.

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

In line with the latest announcement of the Fakultatsleitung Wirtschaftswissenschaften (issued on Sept 29th 2020), this course will be offered entirely in digital form (please ignore the above bookings of PC labs and assume digital lecture rooms). There will be no attendance checks or verifications, however, you will receive assignments during digital lectures, such as quizzes or mini essays (that will be assessed and be part of your overall grading). All examinations will be in a digital format (i.e. no on-site examination).
In order to offer equal conditions to all students and to conform with Federal regulations, there will be no on-site teaching.

Parts of this course use the (fee-based) statistics software STATA. I am currently working with the University of Vienna on a solution that the software can be provided to students; In case this fails, possible workarounds might be to minimize the reliance on STATA or to use an alternative, free software environment.

This course will leverage a combination of different digital teaching tools; In addition to the official digital tools of the University of Vienna (e.g., Big Blue Button), I'll be using additional, well-established digital tools for teaching, such as Zoom, Mentimeter or Padlet. By registering for this course, I assume that you agree with this. Should you have any concerns, please raise them upfront and contact me via email.

  • Wednesday 28.10. 16:45 - 20:00 Digital
  • Thursday 05.11. 15:00 - 18:15 Digital
  • Thursday 12.11. 15:00 - 18:15 Digital
  • Thursday 19.11. 15:00 - 18:15 Digital
  • Thursday 26.11. 15:00 - 18:15 Digital
  • Thursday 03.12. 15:00 - 18:15 Digital
  • Thursday 10.12. 15:00 - 18:15 Digital
  • Monday 11.01. 16:45 - 18:15 Digital
  • Thursday 21.01. 15:00 - 18:15 Digital
  • Thursday 28.01. 15:00 - 18:15 Digital

Aims, contents and method of the course

This course is an introductory class on empirical methods and data analysis. It precedes the follow-up class “Empirical Methods II”.
Students learn the fundamental knowledge and obtain the basic skills required in empirical research. Theoretical sessions cover tools and stages required for running empirical projects (e.g. research design, measurement, methods of data collection, basic descriptive statistics) with a special focus on the pre-evaluation stage of empirical work. Our applied sessions will introduce the students to basic programming skills, allowing them to prepare their data for further analysis using statistical programming software. Students participate actively through home assignments, quizzes and presenting scientific articles from the strategy literature. The obtained theoretical knowledge is applied during a project where students actively develop the necessary (first) steps for conducting their own empirical research projects.
This course uses the statistical software STATA. You can use STATA in the PC labs.

Assessment and permitted materials

Students will be assessed based on their 1) class participation (class work, quizzes, home assignments and a presentation of an empirical paper -> individual, 35% of grade), 2) a written exam (-> individual, 35% of grade) and 3) an empirical project (own paper and a presentation of their own findings -> teamwork in groups, 30% of grade).

Minimum requirements and assessment criteria

Attendance during the first session of this course is mandatory. If students miss the first session without contacting the lecturer via email (at the very latest until 24 hours before the first session), giving a relevant reason/proof (which are: illness=doctor's certificate, exam=confirmation by the examiner) for their absence, they will be deregistered from the course and their place will automatically be assigned to the next in line on the waiting list. Students can miss a maximum of two sessions before the Christmas break (however, need to compensate for that through home assignments). Students cannot miss any of the January sessions (since these are used for presentation and the exam).

In order to pass the course, at least 50% of the total 100% are required. Please note that TURNITIN will be used in order to test all written coursework (e.g. the final project) for possible plagiarism.

Reading list

Lecture slides, complemented by selected articles, online tutorials and videos. The necessary literature will be discussed in class.

Information

Examination topics

Students are required to know and have understood all topics discussed in class and presented on the lecture slides.

Association in the course directory

Last modified: Fr 12.05.2023 00:12